Large Language Models for Code and Compiler Education: A Course-Based Undergraduate Research Experience

This project brings together twenty undergraduate students for a one-month intensive research course during the summer term. Students will explore how large language models can be applied to compiler education by developing small-scale systems that clarify compiler feedback, detect syntax issues, and support conceptual understanding through dialogue. By embedding authentic research into a structured course, the project bridges the gap between education and discovery—allowing students to experience how modern AI relates to the systems they study in theory. It directly supports NM EPSCoR’s SURE Award objectives by expanding undergraduate research engagement, building institutional capacity in AI and computing, and advancing New Mexico’s Science and Technology priorities in intelligent systems and data-driven education.